Nebius Group (NBIS) to Release Quarterly Earnings on Friday
Nebius Group (NASDAQ:NBIS) is set to release its quarterly earnings on April 25, with analysts predicting a loss of $0.41 per share and revenue of $61.55 million. The stock has seen a 2.1% increase, opening at $21.53, with a market cap of $5.07 billion. Analysts have mixed ratings, with DA Davidson lowering its target price from $50 to $30, while BWS Financial maintains a buy rating with a $60 target. The company specializes in AI-driven products and services.
Nebius Group (NASDAQ:NBIS - Get Free Report) is anticipated to issue its quarterly earnings data before the market opens on Friday, April 25th. Analysts expect the company to announce earnings of ($0.41) per share and revenue of $61.55 million for the quarter.
Nebius Group Stock Up 2.1 %
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Shares of NASDAQ NBIS opened at $21.53 on Friday. The company has a market capitalization of $5.07 billion, a PE ratio of -37.77 and a beta of 2.54. The stock's 50 day moving average price is $29.35 and its 200-day moving average price is $27.37. Nebius Group has a twelve month low of $14.09 and a twelve month high of $50.87.
Analyst Ratings Changes
Several analysts have issued reports on NBIS shares. DA Davidson lowered their target price on Nebius Group from $50.00 to $30.00 and set a "buy" rating on the stock in a research note on Monday. BWS Financial reiterated a "buy" rating and issued a $60.00 target price on shares of Nebius Group in a research note on Tuesday, March 4th.
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Read Our Latest Stock Report on Nebius Group
Nebius Group Company Profile
(Get Free Report)Nebius Group N.V., a technology company, builds intelligent products and services powered by machine learning and other technologies to help consumers and businesses navigate the online and offline world. The company's services include Nebius AI, an AI-centric cloud platform that offers infrastructure and computing capability for AI deployment and machine-learning oriented solutions; and Toloka AI that offers generative AI (GenAI) solutions at every stage of the GenAI lifecycle, such as data annotation and generation, model training and fine-tuning, and quality assessment of large language model for accuracy and reliability.
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